Geological Porosity and Permeability Analysis

1. Data Importation

data<-read.csv(file.choose(),header=TRUE)

2. Initial Data Exploration

plot(data$phi.N,data$phi.core.frac)

# 3. Porosity Model Development

porosity_model<-lm(phi.core.frac~phi.N+Facies-1,data=data)
summary(porosity_model)

## 
## Call:
## lm(formula = phi.core.frac ~ phi.N + Facies - 1, data = data)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -0.103530 -0.011573 -0.000206  0.010463  0.102852 
## 
## Coefficients:
##           Estimate Std. Error t value Pr(>|t|)    
## phi.N     0.013364   0.018060    0.74     0.46    
## FaciesF1  0.314805   0.002777  113.37   <2e-16 ***
## FaciesF10 0.207680   0.005072   40.95   <2e-16 ***
## FaciesF2  0.175233   0.009390   18.66   <2e-16 ***
## FaciesF3  0.231939   0.004955   46.81   <2e-16 ***
## FaciesF5  0.272953   0.003914   69.74   <2e-16 ***
## FaciesF7  0.225164   0.008730   25.79   <2e-16 ***
## FaciesF8  0.305884   0.005019   60.94   <2e-16 ***
## FaciesF9  0.264448   0.004825   54.81   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.02326 on 810 degrees of freedom
## Multiple R-squared:  0.9928, Adjusted R-squared:  0.9928 
## F-statistic: 1.246e+04 on 9 and 810 DF,  p-value: < 2.2e-16

4. Corrected Porosity Calculation

corrected_porosity.<-predict(porosity_model,data)

5. Permeability Model Development

permeabilty_model<-lm(data$k.core~corrected_porosity.+Facies-1,data=data)
summary(permeabilty_model)

## 
## Call:
## lm(formula = data$k.core ~ corrected_porosity. + Facies - 1, 
##     data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5613.4  -596.9  -130.3   475.0 10449.1 
## 
## Coefficients:
##                     Estimate Std. Error t value Pr(>|t|)    
## corrected_porosity.  -412352      89814  -4.591 5.11e-06 ***
## FaciesF1              132659      28386   4.673 3.47e-06 ***
## FaciesF10              87869      18969   4.632 4.21e-06 ***
## FaciesF2               73980      16049   4.610 4.69e-06 ***
## FaciesF3               97910      21087   4.643 4.00e-06 ***
## FaciesF5              118916      24729   4.809 1.81e-06 ***
## FaciesF7               95868      20496   4.677 3.40e-06 ***
## FaciesF8              130990      27786   4.714 2.86e-06 ***
## FaciesF9              111324      24050   4.629 4.28e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1546 on 810 degrees of freedom
## Multiple R-squared:  0.7652, Adjusted R-squared:  0.7626 
## F-statistic: 293.2 on 9 and 810 DF,  p-value: < 2.2e-16

6. Corrected Permeability Calculation

corrected_permeabilty.<-predict(permeabilty_model,data)

7. Result Visualization

par(mfrow=(c(1,5)))
plot(data$phi.core.frac,data$depth,ylim =rev(c(5667,6083)),xlim =c (
  0.1570,0.3630), type = "l",lwd=2,xlab = "core porosity",ylab='depth m')

plot(corrected_porosity.,data$depth,ylim =rev(c(5667,6083)),xlim =c (0.1775,
0.3203), type = "l",lwd=2,xlab = "corrected core porosity",ylab='depth m')
plot(data$k.core,data$depth,ylim =rev(c(5667,6083)),xlim =c (0.42,
                                                             
15600.00), type = "l",lwd=2,xlab = " core permeabilty",ylab='depth m')

plot(corrected_permeabilty.,data$depth,ylim =rev(c(5667,6083)),xlim =c (0.42,
15600.00), type = "l",lwd=2,xlab = " corrected core permeabilty",ylab='depth m')

# 8. Facies Analysis

boxplot(depth~Facies,data=data,ylim =rev(c(5667,6083)))